class_docstr: A class that tokenizes and otherwise processes text to be encoded
  by a BERT model.
docstr: Decodes a single list of token ids to tokens
  
  :param id_list: a list of token ids
  :type id_list: List
  :return: a list of tokens
  :rtype: List
docstr_tok: ["Decodes","a","single","list","of","token","ids","to","tokens",":","param","id_list",":","a","list","of","token","ids",":","type","id_list",":","List",":","return",":","a","list","of","tokens",":","rtype",":","List"]
code: def decode_single(self, id_list: List) -> List:
      """Decodes a single list of token ids to tokens
  
      :param id_list: a list of token ids
      :type id_list: List
      :return: a list of tokens
      :rtype: List
      """
      tokenizer = self.get_tokenizer()
      return tokenizer.convert_ids_to_tokens(id_list)
  
file_path: interpret-text/python/interpret_text/experimental/common/preprocessor/bert_preprocessor.py
imports: import pandas
  from typing import List
  from interpret_text.experimental.common.base_explainer import BaseTextPreprocessor
  from transformers import BertTokenizer
label_desc: Use image node_id 3 for calling the BertPreprocessor obj's underlying member method code with example usage: obj.decode_single(id_list) and returns: tokenizer